Integrating Spatial Transcriptomics and Single-Cell RNA-seq Reveals the Gene Expression Profling of the Human Embryonic Liver

Comprehensive circRNA expression profile and hub genes screening during human liver development

BACKGROUND

Understanding the expression of non-coding RNA in the liver during embryonic development provides important insights into liver diseases. Therefore, we investigated circular RNA (circRNA) roles in human liver development, an unexplored research domain.

METHODS

Using high-throughput sequencing and bioinformatics, we analysed foetal liver samples across developmental stages (7-20 weeks post-conception). Differentially expressed (DE) genes were identified and subjected to enrichment analysis using Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG), and Disease Ontology (DO). Modular analysis was performed using the Search Tool for Retrieval of Interacting Genes (STRING), followed by construction of a protein-protein interaction (PPI) network using Cytoscape software. The key genes were screened using Molecular Complex Detection (MCODE). The mRNA levels of hub genes were validated using quantitative reverse transcription polymerase chain reaction (qRT-PCR).

RESULTS

There were 645 DE circRNAs and 5,145 DE mRNAs between human livers at the three growth stages (HB, EH, and LH). It was found that the activity of circRNAs was boosted remarkably in the hepatoblastic stage. Enrichment analysis found they mainly involved in nervous system regulation of liver function, embryonic organ development and digestive system development. In addition, DE circRNAs were primarily involved in the PI3K-AKT, MAPK and calcium pathways, potentially contributing to adult liver diseases. Notably, only hsa_circ_001471 and novel_circ_017382 were simultaneously identified at all stages and were persistently downregulated. A co-expression regulatory network involving these circRNAs was established. Three hub genes (LGR5, FOXL1 and RSPO3) were identified from the PPI network of 167 genes and may play key roles in human liver development. The RT-qPCR validation results were in agreement with the sequencing data.

CONCLUSIONS

Our findings provide the first insights into the roles and regulatory networks of circRNAs in human liver development, laying the groundwork for further investigations of molecular and signalling networks.

Application of scRNA-seq in Dental Research: Seeking Regenerative Clues From the Structure of Tooth and Periodontium in Physical or Pathological States

This review presents a comprehensive overview of single-cell RNA sequencing (scRNA-seq) analyses used to study tooth and periodontal tissues. The intricate cellular composition of both teeth and periodontium are revealed, leading to the identification of new cell types and tracing lineage profiles for each cell type. Herein, we summarize the progression of dental and periodontal tissue formation, tooth homeostasis, and regenerative mechanisms. scRNA-seq analyses have demonstrated that the cellular constituent ratio of dental and periodontal tissues transforms homeostasis or injury repair. Importantly, single-cell data in the diseased tissue demonstrated a change in both cell types and intercellular communication patterns compared to the normal state. These findings provide valuable insights into the underlying disease mechanisms at the cellular level in the context of single-cell vision, thereby facilitating the investigation of potential therapeutic interventions.

Exploring the Spatial Distribution of Interstitial Cells in Kidney Tissue

INTRODUCTION

Interstitial cells are crucial to the development of kidney structure and function, although the mechanism underlying their role in it remains unclear to date. Our previous study identified cell clusters in human fetal kidney tissue, and we further analyzed the interstitial cell cluster within this context.

METHODS

We extracted the barcoded cDNA from tissue samples and prepared spatial transcriptome libraries. Sequencing data were quality-checked, normalized, and clusters were identified using Seurat. Single-cell and spatial data were integrated using multimodal intersection analysis, and cell types were deconvoluted. DEGs in interstitial cells were identified and functionally annotated using DAVID. CellPhoneDB was used to predict ligand-receptor interactions between cell types.

RESULTS

The results of the present study revealed that this cluster of interstitial cells appeared to be scattered in the junction between the cortical and medullary regions. The subsequent Kyoto Encyclopedia of Genes and Genome pathway analysis revealed that the differentially expressed genes (DEGs) in this cluster of interstitial cells were involved in the WNT signaling pathway. The Gene Ontology (GO) analysis revealed that these DEGs were involved in multiple pathways associated with kidney development, with six of the genes (NKD2, TCF21, WNT5A, WNT4, MDK, and SFRP1) associated with kidney development exhibiting significant upregulation. Accordingly, it was inferred that these interstitial cells might be involved in regulating epithelial cell differentiation, ureteral bud development, and morphogenesis. The subsequent cell-cell communication analysis revealed that the cellular crosstalk was primarily regulated mainly by ligand-receptor pairs. Additionally, 17 genes reported to be associated with kidney disease were focused on, and these genes were found to be predominantly expressed in a single-cell type.

CONCLUSION

In summary, the present study revealed the characteristics of a previously identified cluster of interstitial cells in the kidney tissue, thereby providing fresh insights into the process of kidney development.

Spatial genomics: mapping human steatotic liver disease

Metabolic dysfunction-associated steatotic liver disease (MASLD, formerly known as non-alcoholic fatty liver disease) is a leading cause of chronic liver disease worldwide. MASLD can progress to metabolic dysfunction-associated steatohepatitis (MASH, formerly known as non-alcoholic steatohepatitis) with subsequent liver cirrhosis and hepatocellular carcinoma formation. The advent of current technologies such as single-cell and single-nuclei RNA sequencing have transformed our understanding of the liver in homeostasis and disease. The next frontier is contextualizing this single-cell information in its native spatial orientation. This understanding will markedly accelerate discovery science in hepatology, resulting in a further step-change in our knowledge of liver biology and pathobiology. In this Review, we discuss up-to-date knowledge of MASLD development and progression and how the burgeoning field of spatial genomics is driving exciting new developments in our understanding of human liver disease pathogenesis and therapeutic target identification.

PoweREST: Statistical Power Estimation for Spatial Transcriptomics Experiments to Detect Differentially Expressed Genes Between Two Conditions

Recent advancements in Spatial Transcriptomics (ST) have significantly enhanced biological research in various domains. However, the high cost of current ST data generation techniques restricts its application in large-scale population studies. Consequently, there is a pressing need to maximize the use of available resources to achieve robust statistical power. One fundamental question in ST analysis is to detect differentially expressed genes (DEGs) among different conditions using ST data. Such DEG analysis is often performed but the associated power calculation is rarely discussed in the literature. To address this gap, we introduce, PoweREST (https://github.com/lanshui98/PoweREST), a power estimation tool designed to support power calculation of DEG detection with 10X Genomics Visium data. PoweREST enables power estimation both before any ST experiments or after preliminary data are collected, making it suitable for a wide variety of power analyses in ST studies. We also provide a user-friendly, program-free web application (https://lanshui.shinyapps.io/PoweREST/), allowing users to interactively calculate and visualize the study power along with relevant the parameters.

Single-nucleus transcriptome reveals cell dynamic response of liver during the late chick embryonic development

The late embryonic development of the liver, a major metabolic organ, remains poorly characterized at single cell resolution. Here, we used single-nucleus RNA-sequencing (snRNA-seq) to characterize the chicken liver cells at 2 embryonic development time points (E14 and D1). We uncovered 8 cell types including hepatocytes, endothelial cells, hepatic stellate cells, erythrocytes, cholangiocytes, kupffer cells, mesothelial cells, and lymphocytes. And we discovered significant differences in the abundance of different cell types between E14 and D1. Moreover, we characterized the heterogeneity of hepatocytes, endothelial cells, and mesenchymal cells based on the gene regulatory networks of each clusters. Trajectory analyses revealed 128 genes associated with hepatocyte development and function, including apolipoprotein genes involved hepatic lipid metabolism and NADH dehydrogenase subunits involved hepatic oxidative phosphorylation. Furthermore, we identified the differentially expressed genes (DEGs) between E14 and D1 at the cellular levels, which contribute to changes in liver development and function. These DEGs were significantly enriched in PPAR signaling pathways and lipid metabolism related pathways. Our results presented the single-cell mapping of chick embryonic liver at late stages of development and demonstrated the metabolic changes across the 2 age stages at the cellular level, which can help to further study the molecular development mechanism of embryonic liver.

Understanding Macrophage Complexity in Metabolic Dysfunction-Associated Steatotic Liver Disease: Transitioning from the M1/M2 Paradigm to Spatial Dynamics

Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses metabolic dysfunction-associated fatty liver (MASL) and metabolic dysfunction-associated steatohepatitis (MASH), with MASH posing a risk of progression to cirrhosis and hepatocellular carcinoma (HCC). The global prevalence of MASLD is estimated at approximately a quarter of the population, with significant healthcare costs and implications for liver transplantation. The pathogenesis of MASLD involves intrahepatic liver cells, extrahepatic components, and immunological aspects, particularly the involvement of macrophages. Hepatic macrophages are a crucial cellular component of the liver and play important roles in liver function, contributing significantly to tissue homeostasis and swift responses during pathophysiological conditions. Recent advancements in technology have revealed the remarkable heterogeneity and plasticity of hepatic macrophage populations and their activation states in MASLD, challenging traditional classification methods like the M1/M2 paradigm and highlighting the coexistence of harmful and beneficial macrophage phenotypes that are dynamically regulated during MASLD progression. This complexity underscores the importance of considering macrophage heterogeneity in therapeutic targeting strategies, including their distinct ontogeny and functional phenotypes. This review provides an overview of macrophage involvement in MASLD progression, combining traditional paradigms with recent insights from single-cell analysis and spatial dynamics. It also addresses unresolved questions and challenges in this area.

The hematopoietic stem cell expansion niche in fetal liver: Current state of the art and the way forward

Hematopoietic development goes through a number of embryonic sites that host hematopoietic progenitor and stem cells with function required at specific developmental stages. Among embryonic sites, the fetal liver (FL) hosts definitive hematopoietic stem cells (HSCs) capable of engrafting adult hematopoietic system and supports their rapid expansion. Hence, this site provides an excellent model to understand the cellular and molecular components of the machinery involved in HSC-proliferative events, leading to their overall expansion. It has been unequivocally established that extrinsic regulators orchestrate events that maintain HSC function. Although most studies on extrinsic regulation of HSC function are targeted at adult bone marrow (BM) hematopoiesis, little is known about how FL HSC function is regulated by their microniche. This review provides the current state of our understanding on molecular and cellular niche factors that support FL hematopoiesis.

Integration tools for scRNA-seq data and spatial transcriptomics sequencing data

Numerous methods have been developed to integrate spatial transcriptomics sequencing data with single-cell RNA sequencing (scRNA-seq) data. Continuous development and improvement of these methods offer multiple options for integrating and analyzing scRNA-seq and spatial transcriptomics data based on diverse research inquiries. However, each method has its own advantages, limitations and scope of application. Researchers need to select the most suitable method for their research purposes based on the actual situation. This review article presents a compilation of 19 integration methods sourced from a wide range of available approaches, serving as a comprehensive reference for researchers to select the suitable integration method for their specific research inquiries. By understanding the principles of these methods, we can identify their similarities and differences, comprehend their applicability and potential complementarity, and lay the foundation for future method development and understanding. This review article presents 19 methods that aim to integrate scRNA-seq data and spatial transcriptomics data. The methods are classified into two main groups and described accordingly. The article also emphasizes the incorporation of High Variance Genes in annotating various technologies, aiming to obtain biologically relevant information aligned with the intended purpose.

Emerging Roles of Spatial Transcriptomics in Liver Research

Spatial transcriptomics, leveraging sequencing- and imaging-based techniques, has emerged as a groundbreaking technology for mapping gene expression within the complex architectures of tissues. This approach provides an in-depth understanding of cellular and molecular dynamics across various states of healthy and diseased livers. Through the integration of sophisticated bioinformatics strategies, it enables detailed exploration of cellular heterogeneity, transitions in cell states, and intricate cell-cell interactions with remarkable precision. In liver research, spatial transcriptomics has been particularly revelatory, identifying distinct zonated functions of hepatocytes that are crucial for understanding the metabolic and detoxification processes of the liver. Moreover, this technology has unveiled new insights into the pathogenesis of liver diseases, such as the role of lipid-associated macrophages in steatosis and endothelial cell signals in liver regeneration and repair. In the domain of liver cancer, spatial transcriptomics has proven instrumental in delineating intratumor heterogeneity, identifying supportive microenvironmental niches and revealing the complex interplay between tumor cells and the immune system as well as susceptibility to immune checkpoint inhibitors. In conclusion, spatial transcriptomics represents a significant advance in hepatology, promising to enhance our understanding and treatment of liver diseases.

Single-cell Technologies Provide Novel Insights into Liver Physiology and Pathology

The liver is the largest glandular organ in the body and has a unique distribution of cells and biomolecules. However, the treatment outcome of end-stage liver disease is extremely poor. Single-cell sequencing is a new advanced and powerful technique for identifying rare cell populations and biomolecules by analyzing the characteristics of gene expression between individual cells. These cells and biomolecules might be used as potential targets for immunotherapy of liver diseases and contribute to the development of precise individualized treatment. Compared to whole-tissue RNA sequencing, single-cell RNA sequencing (scRNA-seq) or other single-cell histological techniques have solved the problem of cell population heterogeneity and characterize molecular changes associated with liver diseases with higher accuracy and resolution. In this review, we comprehensively summarized single-cell approaches including transcriptomic, spatial transcriptomic, immunomic, proteomic, epigenomic, and multiomic technologies, and described their application in liver physiology and pathology. We also discussed advanced techniques and recent studies in the field of single-cell; our review might provide new insights into the pathophysiological mechanisms of the liver to achieve precise and individualized treatment of liver diseases.

Single-nucleus transcriptome sequencing reveals hepatic cell atlas in pigs

BACKGROUND

As the largest substantive organ of animals, the liver plays an essential role in the physiological processes of digestive metabolism and immune defense. However, the cellular composition of the pig liver remains poorly understood. This investigation used single-nucleus RNA sequencing technology to identify cell types from liver tissues of pigs, providing a theoretical basis for further investigating liver cell types in pigs.

RESULTS

The analysis revealed 13 cells clusters which were further identified 7 cell types including endothelial cells, T cells, hepatocytes, Kupffer cells, stellate cells, B cells, and cholangiocytes. The dominant cell types were endothelial cells, T cells and hepatocytes in the liver tissue of Dahe pigs and Dahe black pigs, which accounts for about 85.76% and 82.74%, respectively. The number of endothelial cells was higher in the liver tissue of Dahe pigs compared to Dahe black pigs, while the opposite tendency was observed for T cells. Moreover, functional enrichment analysis demonstrated that the differentially expressed genes in pig hepatic endothelial cells were significantly enriched in the protein processing in endoplasmic reticulum, MAPK signaling pathway, and FoxO signaling pathway. Functional enrichment analysis demonstrated that the differentially expressed genes in pig hepatic T cells were significantly enriched in the thyroid hormone signaling pathway, B cell receptor signaling pathway, and focal adhesion. Functional enrichment analysis demonstrated that the differentially expressed genes in pig hepatic hepatocytes were significantly enriched in the metabolic pathways.

CONCLUSIONS

In summary, this study provides a comprehensive cell atlas of porcine hepatic tissue. The number, gene expression level and functional characteristics of each cell type in pig liver tissue varied between breeds.

A Gene Correlation Measurement Method for Spatial Transcriptome Data Based on Partitioning and Distribution

Spatial transcriptome (ST) technology provides both the spatial location and transcriptional profile of spots, as well as tissue images. ST data can be utilized to construct gene regulatory networks, which can help identify gene modules that facilitate the understanding of biological processes such as cell communication. Correlation measurement is the core basis for constructing a gene regulatory network. However, due to the high noise and sparsity in ST data, common correlation measurement methods such as the Pearson correlation coefficient (PCC) and Spearman correlation coefficient (SPCC) are not suitable. In this work, a new gene correlation measurement method called STgcor is proposed. STgcor defines vertexes as spots in a two-dimensional coordinate plane consisting of axes X and Y from the gene pair (X and Y). The joint probability density of Gaussian distribution of the gene pair (X and Y) is calculated to identify and eliminate outliers. To overcome sparsity, the degree, trend, and location of the distribution of vertexes are used to measure the correlation between gene pairs (X, Y). To validate the performance of the STgcor method, it is compared with the PCC and SPCC in a weighted coexpression network analysis method using two ST datasets of breast cancer and prostate cancer. The gene modules identified by these methods are then compared and analyzed. The results show that the STgcor method detects some special gene modules and cancer-related pathways that cannot be detected by the other two methods.

Spatial Single-Cell Technologies for Exploring Gastrointestinal Tissue Transcriptome

In the gastrointestinal (GI) system, like in other organ systems, the histological structure is a key determinant of physiological function. Tissues form multiple layers in the GI tract to perform their specialized functions in secretion, absorption, and motility. Even at the single layer, the heterogeneous cell population performs a diverse range of digestive or regulatory functions. Although many details of such functions at the histological and cell biological levels were revealed by traditional methods such as cell sorting, isolation, and culture, as well as histological methods such as immunostaining and RNA in situ hybridization, recent advances in spatial single-cell technologies could further contribute to our understanding of the molecular makeup of GI histological structures by providing a genome-wide overview of how different genes are expressed across individual cells and tissue layers. The current minireview summarizes recent advances in the spatial transcriptomics field and discusses how such technologies can promote our understanding of GI physiology. © 2023 American Physiological Society. Compr Physiol 13:4709-4718, 2023.

Advances in spatial transcriptomics and related data analysis strategies

Spatial transcriptomics technologies developed in recent years can provide various information including tissue heterogeneity, which is fundamental in biological and medical research, and have been making significant breakthroughs. Single-cell RNA sequencing (scRNA-seq) cannot provide spatial information, while spatial transcriptomics technologies allow gene expression information to be obtained from intact tissue sections in the original physiological context at a spatial resolution. Various biological insights can be generated into tissue architecture and further the elucidation of the interaction between cells and the microenvironment. Thus, we can gain a general understanding of histogenesis processes and disease pathogenesis, etc. Furthermore, in silico methods involving the widely distributed R and Python packages for data analysis play essential roles in deriving indispensable bioinformation and eliminating technological limitations. In this review, we summarize available technologies of spatial transcriptomics, probe into several applications, discuss the computational strategies and raise future perspectives, highlighting the developmental potential.

Lectin-based carbohydrate profile of megakaryocytes in murine fetal liver during development

Hematopoiesis is the process by which blood cells are generated. During embryonic development, these cells migrate through different organs until they reach the bone marrow, their definitive place in adulthood. Around E10.5, the fetal liver starts budding from the gut, where first hematopoietic cells arrive and expand. Hematopoietic cell migration occurs through cytokine stimulation, receptor expression, and glycosylation patterns on the cell surface. In addition, carbohydrates can modulate different cell activation states. For this reason, we aimed to characterize and quantify fetal megakaryocytic cells in mouse fetal liver according to their glycan residues at different gestational ages through lectins. Mouse fetuses between E11.5 and E18.5 were formalin-fixed and, paraffin-embedded, for immunofluorescence analysis using confocal microscopy. The results showed that the following sugar residues were expressed in proliferating and differentiating megakaryocytes in the fetal liver at different gestational ages: α-mannose, α-glucose, galactose, GlcNAc, and two types of complex oligosaccharides. Megakaryocytes also showed three proliferation waves during liver development at E12.5, E14.5, and E18.5. Additionally, the lectins that exhibited high and specific pattern intensities at liver capsules and vessels were shown to be a less time-consuming and robust alternative alternative to conventional antibodies for displaying liver structures such as capsules and vessels, as well as for megakaryocyte differentiation in the fetal liver.

Advances and Challenges in Spatial Transcriptomics for Developmental Biology

Development from single cells to multicellular tissues and organs involves more than just the exact replication of cells, which is known as differentiation. The primary focus of research into the mechanism of differentiation has been differences in gene expression profiles between individual cells. However, it has predominantly been conducted at low throughput and bulk levels, challenging the efforts to understand molecular mechanisms of differentiation during the developmental process in animals and humans. During the last decades, rapid methodological advancements in genomics facilitated the ability to study developmental processes at a genome-wide level and finer resolution. Particularly, sequencing transcriptomes at single-cell resolution, enabled by single-cell RNA-sequencing (scRNA-seq), was a breath-taking innovation, allowing scientists to gain a better understanding of differentiation and cell lineage during the developmental process. However, single-cell isolation during scRNA-seq results in the loss of the spatial information of individual cells and consequently limits our understanding of the specific functions of the cells performed by different spatial regions of tissues or organs. This greatly encourages the emergence of the spatial transcriptomic discipline and tools. Here, we summarize the recent application of scRNA-seq and spatial transcriptomic tools for developmental biology. We also discuss the limitations of current spatial transcriptomic tools and approaches, as well as possible solutions and future prospects.

SPASCER: spatial transcriptomics annotation at single-cell resolution

In recent years, the explosive growth of spatial technologies has enabled the characterization of spatial heterogeneity of tissue architectures. Compared to traditional sequencing, spatial transcriptomics reserves the spatial information of each captured location and provides novel insights into diverse spatially related biological contexts. Even though two spatial transcriptomics databases exist, they provide limited analytical information. Information such as spatial heterogeneity of genes and cells, cell-cell communication activities in space, and the cell type compositions in the microenvironment are critical clues to unveil the mechanism of tumorigenesis and embryo differentiation. Therefore, we constructed a new spatial transcriptomics database, named SPASCER (https://ccsm.uth.edu/SPASCER), designed to help understand the heterogeneity of tissue organizations, region-specific microenvironment, and intercellular interactions across tissue architectures at multiple levels. SPASCER contains datasets from 43 studies, including 1082 sub-datasets from 16 organ types across four species. scRNA-seq was integrated to deconvolve/map spatial transcriptomics, and processed with spatial cell-cell interaction, gene pattern and pathway enrichment analysis. Cell-cell interactions and gene regulation network of scRNA-seq from matched spatial transcriptomics were performed as well. The application of SPASCER will provide new insights into tissue architecture and a solid foundation for the mechanistic understanding of many biological processes in healthy and diseased tissues.

Roles of Skeletal Muscle in Development: A Bioinformatics and Systems Biology Overview

The ability to assess various cellular events consequent to perturbations, such as genetic mutations, disease states and therapies, has been recently revolutionized by technological advances in multiple "omics" fields. The resulting deluge of information has enabled and necessitated the development of tools required to both process and interpret the data. While of tremendous value to basic researchers, the amount and complexity of the data has made it extremely difficult to manually draw inference and identify factors key to the study objectives. The challenges of data reduction and interpretation are being met by the development of increasingly complex tools that integrate disparate knowledge bases and synthesize coherent models based on current biological understanding. This chapter presents an example of how genomics data can be integrated with biological network analyses to gain further insight into the developmental consequences of genetic perturbations. State of the art methods for conducting similar studies are discussed along with modern methods used to analyze and interpret the data.

Spatially resolved transcriptomics: advances and applications

Spatial transcriptomics, which is capable of both measuring all gene activity in a tissue sample and mapping where this activity occurs, is vastly improving our understanding of biological processes and disease. The field has expanded rapidly in recent years, and the development of several new technologies has resulted in spatially resolved transcriptomics (SRT) becoming highly multiplexed, high-resolution, and high-throughput. Here, we summarize and compare the major methods of SRT, including imaging-based methods, sequencing-based methods, and in situ sequencing methods. We also highlight some typical applications of SRT in neuroscience, cancer biology, developmental biology, and hematology. Finally, we discuss future possibilities for improving spatially resolved transcriptomic methods and the expected applications of such methods, especially in the adult bone marrow, anticipating that new developments will unlock the full potential of spatially resolved multi-omics in both biological research and the clinic.

Narrative engineering of the liver

Liver organoids are primary or pluripotent stem cell-derived three-dimensional structures that recapitulate regenerative or ontogenetic processes in vitro towards biomedical applications including disease modelling and diagnostics, drug safety and efficacy prediction, and therapeutic use. The cellular composition and structural organization of liver organoids may vary depending on the goal at hand, and the key challenge in general is to direct their development in a rational and controlled fashion for gaining targeted maturity, reproducibility, and scalability. Such endeavor begins with a detailed understanding of the biological processes in space and time behind hepatogenesis, followed by precise translation of these narrative processes through a bioengineering approach. Here, we discuss advancements in liver organoid technology through the lens of 'narrative engineering' in an attempt to synergize evolving understanding around molecular and cellular landscape governing hepatogenesis with engineering-inspired approaches for organoidgenesis.

Analysis of Gene Expression and TCR/B Cell Receptor Profiling of Immune Cells in Primary Sjögren's Syndrome by Single-Cell Sequencing

Primary Sjögren's syndrome (pSS) is a chronic autoimmune disease that is estimated to affect 35 million people worldwide and is characterized by lymphocytic infiltration, elevated circulating autoantibodies, and proinflammatory cytokines. The key immune cell subset changes and the TCR/BCR repertoire alterations in pSS patients remain unclear. In this study, we sought to comprehensively characterize the transcriptional changes in PBMCs of pSS patients by single-cell RNA sequencing and single-cell V(D)J sequencing. Naive CD8⁺ T cells and mucosal-associated invariant T cells were markedly decreased but regulatory T cells were increased in pSS patients. There were a large number of differentially expressed genes shared by multiple subpopulations of T cells and B cells. Abnormal signaling pathways, including Ag processing and presentation, the BCR signaling pathway, the TCR signaling pathway, and Epstein-Barr virus infection, were highly enriched in pSS patients. Moreover, there were obvious differences in the CD30, FLT3, IFN-II, IL-1, IL-2, IL-6, IL-10, RESISTIN, TGF-β, TNF, and VEGF signaling networks between pSS patients and healthy controls. Single-cell TCR and BCR repertoire analysis showed that there was a lower diversity of T cells in pSS patients than in healthy controls; however, there was no significant difference in the degree of clonal expansion, CDR3 length distribution, or degree of sequence sharing. Notably, our results further emphasize the functional importance of αβ pairing in determining Ag specificity. In conclusion, our analysis provides a comprehensive single-cell map of gene expression and TCR/BCR profiles in pSS patients for a better understanding of the pathogenesis, diagnosis, and treatment of pSS.

Dynamic 3D genome reorganization during development and metabolic stress of the porcine liver

Liver development is a complex process that is regulated by a series of signaling pathways. Three-dimensional (3D) chromatin architecture plays an important role in transcriptional regulation; nonetheless, its dynamics and role in the rapid transition of core liver functions during development and obesity-induced metabolic stress remain largely unexplored. To investigate the dynamic chromatin architecture during liver development and under metabolic stress, we generated high-resolution maps of chromatin architecture for porcine livers across six major developmental stages (from embryonic day 38 to the adult stage) and under a high-fat diet-induced obesity. The characteristically loose chromatin architecture supports a highly plastic genome organization during early liver development, which fundamentally contributes to the rapid functional transitions in the liver after birth. We reveal the multi-scale reorganization of chromatin architecture and its influence on transcriptional regulation of critical signaling processes during liver development, and show its close association with transition in hepatic functions (i.e., from hematopoiesis in the fetus to metabolism and immunity after birth). The limited changes in chromatin structure help explain the observed metabolic adaptation to excessive energy intake in pigs. These results provide a global overview of chromatin architecture dynamics associated with the transition of physiological liver functions between prenatal development and postnatal maturation, and a foundational resource that allows for future in-depth functional characterization.

Hepatic fibrosis 2022: Unmet needs and a blueprint for the future

Steady progress over four decades toward understanding the pathogenesis and clinical consequences of hepatic fibrosis has led to the expectation of effective antifibrotic drugs, yet none has been approved. Thus, an assessment of the field is timely, to clarify priorities and accelerate progress. Here, we highlight the successes to date but, more importantly, identify gaps and unmet needs, both experimentally and clinically. These include the need to better define cell-cell interactions and etiology-specific elements of fibrogenesis and their link to disease-specific drivers of portal hypertension. Success in treating viral hepatitis has revealed the remarkable capacity of the liver to degrade scar in reversing fibrosis, yet we know little of the mechanisms underlying this response. Thus, there is an exigent need to clarify the cellular and molecular mechanisms of fibrosis regression in order for therapeutics to mimic the liver's endogenous capacity. Better refined and more predictive in vitro and animal models will hasten drug development. From a clinical perspective, current diagnostics are improving but not always biologically plausible or sufficiently accurate to supplant biopsy. More urgently, digital pathology methods that leverage machine learning and artificial intelligence must be validated in order to capture more prognostic information from liver biopsies and better quantify the response to therapies. For more refined treatment of NASH, orthogonal approaches that integrate genetic, clinical, and pathological data sets may yield treatments for specific subphenotypes of the disease. Collectively, these and other advances will strengthen and streamline clinical trials and better link histologic responses to clinical outcomes.

Organ-Specific Endothelial Cell Differentiation and Impact of Microenvironmental Cues on Endothelial Heterogeneity

Endothelial cells throughout the body are heterogeneous, and this is tightly linked to the specific functions of organs and tissues. Heterogeneity is already determined from development onwards and ranges from arterial/venous specification to microvascular fate determination in organ-specific differentiation. Acknowledging the different phenotypes of endothelial cells and the implications of this diversity is key for the development of more specialized tissue engineering and vascular repair approaches. However, although novel technologies in transcriptomics and proteomics are facilitating the unraveling of vascular bed-specific endothelial cell signatures, still much research is based on the use of insufficiently specialized endothelial cells. Endothelial cells are not only heterogeneous, but their specialized phenotypes are also dynamic and adapt to changes in their microenvironment. During the last decades, strong collaborations between molecular biology, mechanobiology, and computational disciplines have led to a better understanding of how endothelial cells are modulated by their mechanical and biochemical contexts. Yet, because of the use of insufficiently specialized endothelial cells, there is still a huge lack of knowledge in how tissue-specific biomechanical factors determine organ-specific phenotypes. With this review, we want to put the focus on how organ-specific endothelial cell signatures are determined from development onwards and conditioned by their microenvironments during adulthood. We discuss the latest research performed on endothelial cells, pointing out the important implications of mimicking tissue-specific biomechanical cues in culture.

Genetic and Cellular Contributions to Liver Regeneration

The regenerative capabilities of the liver represent a paradigm for understanding tissue repair in solid organs. Regeneration after partial hepatectomy in rodent models is well understood, while regeneration in the context of clinically relevant chronic injuries is less studied. Given the growing incidence of fatty liver disease, cirrhosis, and liver cancer, interest in liver regeneration is increasing. Here, we will review the principles, genetics, and cell biology underlying liver regeneration, as well as new approaches being used to study heterogeneity in liver tissue maintenance and repair.